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Store Reasoning Trace

memorix_store_reasoning

Document technical decisions with rationale, alternatives, and expected outcomes to create a searchable reasoning record. Use when choosing between approaches or solving complex problems.

Instructions

Store a reasoning trace — WHY you chose this approach, what alternatives you considered, and what outcome you expect. This creates a searchable record of your decision-making process. Use this when making non-trivial technical decisions, choosing between approaches, or solving complex problems. Unlike regular memories that record WHAT happened, reasoning memories record HOW you thought about it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
risksNoKnown risks or potential downsides
conceptsNoRelated technical concepts
decisionYesWhat was decided or chosen
rationaleYesWhy this approach was chosen over alternatives
entityNameYesThe entity this reasoning applies to (e.g., "auth-module", "database-schema")
constraintsNoConstraints that influenced the decision (time, perf, compat, etc.)
alternativesNoOther options that were considered
filesModifiedNoFiles related to this reasoning
relatedCommitsNoGit commit hashes this reasoning explains (links ground truth ↔ reasoning)
expectedOutcomeNoWhat outcome is expected from this decision
relatedEntitiesNoOther entity names this reasoning relates to (cross-references)
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. It describes creating a searchable record, implying a write operation with no destructive side effects. Additional detail (e.g., whether it appends or overwrites) could improve transparency, but current description is sufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, front-loaded with the core purpose, then contrasts with sibling tool, then states common use cases. No redundancies or unnecessary detail; every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 11 parameters, no output schema, and no annotations, the description clearly explains the tool's purpose and when to use it. The schema covers parameter details, so the description sufficiently bridges the gap for an agent to understand context and invoke correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the schema already documents parameters. The description adds value by explaining the overall purpose (recording decision rationale, alternatives, outcomes), which contextualizes individual parameters like 'rationale', 'alternatives', and 'expectedOutcome' beyond their lone schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('store reasoning trace') and resource, clearly distinguishing from sibling tools like 'memorix_store' (records WHAT happened) by emphasizing it records HOW you thought. It also contrasts with 'memorix_search_reasoning'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use: 'non-trivial technical decisions', 'choosing between approaches', 'solving complex problems'. Contrasts with regular memories that record WHAT happened, providing clear guidance on when not to use this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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